Low-Complexity Method of Weighted Subspace Fitting for Direction Estimation

Abstract

In this paper, we consider a low-complexity method of weighted subspace fitting (WSF) for direction-of-arrival (DOA) estimation. With the properties of the multi-stage wiener filter (MSWF), we derive a novel criterion function for the WSF method without the estimate of an array covariance matrix and its eigen-decomposition. A new approach for noise variance estimation is also proposed. Numerical results indicate that by selecting a specific weighting matrix, the low-complexity WSF estimator can provide the comparable estimation performance with the conventional WSF method.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2005
Accession Number
ADA503673

Entities

People

  • Lei Huang
  • Linrang Zhang
  • Shunjun Wu

Organizations

  • Xidian University

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Angle Of Arrival
  • Arrays
  • Background Noise
  • Computational Complexity
  • Covariance
  • Decomposition
  • Eigenvalues
  • Electrical Engineering
  • Equations
  • Estimators
  • Filters
  • Matched Filters
  • Radar Signals
  • Signal Processing
  • Statistical Analysis

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.